| 1. |
- Ali Khan, N., et al.
(författare)
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Direction of arrival estimation using adaptive directional time-frequency distributions
- 2018
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Ingår i: Multidimensional systems and signal processing. - : Springer-Verlag New York. - 0923-6082 .- 1573-0824. ; 29:2, s. 503-521
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Tidskriftsartikel (refereegranskat)abstract
- Time-frequency distributions (TFDs) allow direction of arrival (DOA) estimation algorithms to be used in scenarios when the total number of sources are more than the number of sensors. The performance of such time-frequency (t-f) based DOA estimation algorithms depends on the resolution of the underlying TFD as a higher resolution TFD leads to better separation of sources in the t-f domain. This paper presents a novel DOA estimation algorithm that uses the adaptive directional t-f distribution (ADTFD) for the analysis of close signal components. The ADTFD optimizes the direction of kernel at each point in the t-f domain to obtain a clear t-f representation, which is then exploited for DOA estimation. Moreover, the proposed methodology can also be applied for DOA estimation of sparse signals. Experimental results indicate that the proposed DOA algorithm based on the ADTFD outperforms other fixed and adaptive kernel based DOA algorithms.
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| 2. |
- Grip, Niklas, et al.
(författare)
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A discrete model for efficient analysis of time-varying narrowband communication channels
- 2008
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Ingår i: Multidimensional systems and signal processing. - : Springer Science and Business Media LLC. - 0923-6082 .- 1573-0824. ; 19:1, s. 3-40
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Tidskriftsartikel (refereegranskat)abstract
- We derive an efficient numerical algorithm for the analysis of certain classes of Hilbert-Schmidt operators that naturally occur in models of wireless radio and sonar communications channels. We show that many narrowband finite lifelength systems such as wireless radio communications can be well modelled by smooth and compactly supported spreading functions. Further, we exploit this fact to derive a fast algorithm for computing the matrix representation of such operators with respect to well time-frequency localized Gabor bases (such as pulseshaped OFDM bases). Hereby we use a minimum of approximations, simplifications, and assumptions on the channel. Moreover, we use a multivariate setting to allow for applications to, for example, antenna arrays. The derived algorithm and software can be used, for example, for comparing how different system settings and pulse shapes affect the diagonalization properties of an OFDM system acting on a given channel.
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| 3. |
- Larsson, Erik G., et al.
(författare)
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Fast Implementation of Two-Dimensional APES and CAPON Spectral Estimators
- 2002
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Ingår i: Multidimensional systems and signal processing. - 0923-6082 .- 1573-0824. ; 13:1, s. 35-53
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Tidskriftsartikel (refereegranskat)abstract
- The matched-filterbank spectral estimators APES and CAPON have recently received considerable attention in a number of applications. Unfortunately, their computational complexity tends to limit their usage in several cases – a problem that has previously been addressed by different authors. In this paper, we introduce a novel approach to the computation of the APES and CAPON spectra, which leads to a computational method that is considerably faster than all existing techniques. The new implementations of APES and CAPON are called fast APES and fast CAPON, respectively, and are developed for the two-dimensional case, with the one-dimensional case as a special case. Numerical examples are provided to demonstrate the application of APES to synthetic aperture radar (SAR) imaging, and to illustrate the reduction in computational complexity provided by our method.
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| 4. |
- Li, J, et al.
(författare)
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An efficient algorithm for two-dimensional frequency estimation
- 1996
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Ingår i: MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING. - : KLUWER ACADEMIC PUBL. - 0923-6082. ; 7:2, s. 151-178
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. We derive the theoretical performance of the 2D-MODE estimator and show that it is asymptotically statistically efficient unde
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| 5. |
- Li, JA, et al.
(författare)
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One-dimensional MODE algorithm for two-dimensional frequency estimation
- 1997
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Ingår i: MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING. - : KLUWER ACADEMIC PUBL. - 0923-6082. ; 8:4, s. 449-468
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In this paper, we describe how the computationally efficient one-dimensional MODE (ID-MODE) algorithm can be used to estimate the frequencies of two-dimensional complex sinusoids. We show that the ID-MODE algorithm is computationally more efficient than t
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| 6. |
- Wahlberg, Patrik, et al.
(författare)
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Approximate time-variable coherence analysis of multichannel signals
- 2002
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Ingår i: Multidimensional Systems and Signal Processing. - Norwell : Kluwer Academic Publishers. - 0923-6082 .- 1573-0824. ; 13:3, s. 237-264
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Tidskriftsartikel (refereegranskat)abstract
- We present a new method for signal extraction from noisy multichannel epileptic seizure onset EEG signals. These signals are non-stationary which makes time-invariant filtering unsuitable. The new method assumes a signal model and performs denoising by filtering the signal of each channel using a time-variable filter which is an estimate of the Wiener filter. The approximate Wiener filters are obtained using the time-frequency coherence functions between all channel pairs, and a fix-point algorithm. We estimate the coherence functions using the multiple window method, after which the fix-point algorithm is applied. Simulations indicate that this method improves upon its restriction to assumed stationary signals for realistically non-stationary data, in terms of mean square error, and we show that it can also be used for time-frequency representation of noisy multichannel signals. The method was applied to two epileptic seizure onset signals, and it turned out that the most informative output of the method are the filters themselves studied in the time-frequency domain. They seem to reveal hidden features of the epileptic signal which are otherwise invisible. This algorithm can be used as preprocessing for seizure onset EEG signals prior to time-frequency representation and manual or algorithmic pattern classification.
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